INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLS
The current potential market demand with ever-changing situations and conditions must be managed properly to find out the potential market demand in the future. Rumah Warna Yogyakarta is one of the manufacturing industry players that has experienced fluctuations in market demand, even tending to dec...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Pattimura
2024-10-01
|
| Series: | Barekeng |
| Subjects: | |
| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12427 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850194491293564928 |
|---|---|
| author | Sukma Anindita Rahmadi Yotenka |
| author_facet | Sukma Anindita Rahmadi Yotenka |
| author_sort | Sukma Anindita |
| collection | DOAJ |
| description | The current potential market demand with ever-changing situations and conditions must be managed properly to find out the potential market demand in the future. Rumah Warna Yogyakarta is one of the manufacturing industry players that has experienced fluctuations in market demand, even tending to decline from the end of 2021 to mid-2022. Data was obtained from the database and direct interviews with Rumah Warna in Yogyakarta from November 2021 to November 2022. This study aims to determine the prediction of product demand for Rumah Warna Yogyakarta in the next period, so that companies can carry out production planning strategies to minimize production cost. Product demand prediction is carried out using the Grey System method of the GM (1,1) model. Then proceed with the heuristic aggregate planning method that focuses on overtime control and subcontracting control. Based on the results of the analysis, the Grey System GM (1,1) method produces good prediction accuracy of 9.231%. The best aggregate planning method is the overtime control where Rumah Warna Yogyakarta can reduce costs by Rp 351,258,758 when compared to the subcontracting control method. |
| format | Article |
| id | doaj-art-04670c2f9add4b44889efba9794af26c |
| institution | OA Journals |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-04670c2f9add4b44889efba9794af26c2025-08-20T02:13:59ZengUniversitas PattimuraBarekeng1978-72272615-30172024-10-011842263227210.30598/barekengvol18iss4pp2263-227212427INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLSSukma Anindita0Rahmadi Yotenka1Department of Statistics, Faculty of Mathematics and Science, Universitas Islam Indonesia, IndonesiaDepartment of Statistics, Faculty of Mathematics and Science, Universitas Islam Indonesia, IndonesiaThe current potential market demand with ever-changing situations and conditions must be managed properly to find out the potential market demand in the future. Rumah Warna Yogyakarta is one of the manufacturing industry players that has experienced fluctuations in market demand, even tending to decline from the end of 2021 to mid-2022. Data was obtained from the database and direct interviews with Rumah Warna in Yogyakarta from November 2021 to November 2022. This study aims to determine the prediction of product demand for Rumah Warna Yogyakarta in the next period, so that companies can carry out production planning strategies to minimize production cost. Product demand prediction is carried out using the Grey System method of the GM (1,1) model. Then proceed with the heuristic aggregate planning method that focuses on overtime control and subcontracting control. Based on the results of the analysis, the Grey System GM (1,1) method produces good prediction accuracy of 9.231%. The best aggregate planning method is the overtime control where Rumah Warna Yogyakarta can reduce costs by Rp 351,258,758 when compared to the subcontracting control method.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12427aggregate planningdemandgrey systempredictionproduction cost |
| spellingShingle | Sukma Anindita Rahmadi Yotenka INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLS Barekeng aggregate planning demand grey system prediction production cost |
| title | INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLS |
| title_full | INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLS |
| title_fullStr | INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLS |
| title_full_unstemmed | INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLS |
| title_short | INTEGRATED FORECASTING AND AGGREGATE PLANNING FOR PRODUCTION OPTIMIZATION: A COMPARATIVE ANALYSIS OF OVERTIME AND SUBCONTRACTING CONTROLS |
| title_sort | integrated forecasting and aggregate planning for production optimization a comparative analysis of overtime and subcontracting controls |
| topic | aggregate planning demand grey system prediction production cost |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12427 |
| work_keys_str_mv | AT sukmaanindita integratedforecastingandaggregateplanningforproductionoptimizationacomparativeanalysisofovertimeandsubcontractingcontrols AT rahmadiyotenka integratedforecastingandaggregateplanningforproductionoptimizationacomparativeanalysisofovertimeandsubcontractingcontrols |